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Julie Babinard, World Bank Kinnon Scott, World Bank.

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Presentation on theme: "Julie Babinard, World Bank Kinnon Scott, World Bank."— Presentation transcript:

1 Julie Babinard, World Bank Kinnon Scott, World Bank

2  Access to affordable, reliable and safe transport is critical element for economic growth and poverty reduction  Transport planning typically not addressing differences in men and women travel needs  Social and economic roles of women: ◦ Earnings opportunities (jobs, markets ) ◦ Household and domestic work (Child-rearing; resources & food) ◦ Access to social and health services

3  Access to fewer transport choices ◦ (Venter et al. 2007; Odufuwa 2007; Srinivasan 2002)  Spend more on transport ◦ (Kamuhanda and Schmidt 2009; Srinavasan 2002)  Complex travel patterns ◦ (Anand and Tiwari 2006; Odufuwa 2005; Abidemi 2002; Rosenbloom 1995; Malmberg-Calvo 1994; Hanson and Hanson 1980;)  Quality and security concerns ◦ (Okoko 2007)

4 1. Access to transport by women 2. Affordability 3. Journey length and reasons for travel 4. Quality of transport  How to fill in the gaps?

5  “Stand alone” surveys of transport users or households ◦ Costly to carry out ◦ Often one-off (not part of any system of data collection in a country) ◦ Urban  National household surveys ◦ Many countries carry out a range of surveys ◦ Comparable across time, or across countries  Can existing household surveys in developing countries inform transportation policy?

6  Variety of surveys are carried out  Selection criteria: Frequency of implementation (across countries and across time) Data collected at the individual level Our assessment, a priori, of potential usefulness

7  Living Standards Measurement Study Surveys (LSMS)  Income and Expenditure /Household Budget Surveys (IES/HBS)  Demographic and Health Surveys (DHS)  Multiple Indicator Cluster Surveys (MICS

8  Goal  new, better quality data for public policy research on household behavior, household-policy interactions  Focus on welfare- (multi-topic) --causes  Data on individuals and households  Complementary data on community, prices, facilities

9  Living Standards Measurement Study Surveys (LSMS)  Income and Expenditure /Household Budget Surveys (IES/HBS)  Demographic and Health Surveys (DHS)  Multiple Indicator Cluster Surveys (MICS

10  Goal  household expenditures, weights for consumer price indices, inputs for national accounts  Some demographics, education and employment data  Data are always collected at the household level  Some contain individual expenditure diaries.  Frequent: annually in Eastern Europe, every five years in other parts Latin America, for ex.

11  Living Standards Measurement Study Surveys (LSMS)  Income and Expenditure /Household Budget Surveys (IES/HBS)  Demographic and Health Surveys (DHS)  Multiple Indicator Cluster Surveys (MICS

12  Goal  data for policy on health, primarily maternal and infant health, fertility, family planning, nutrition, assets, education  Data at individual level and household level  Implemented systematically in many developing countries, multiple rounds  Comparable across countries and time

13  Living Standards Measurement Study Surveys (LSMS)  Income and Expenditure /Household Budget Surveys (IES/HBS)  Demographic and Health Surveys (DHS)  Multiple Indicator Cluster Surveys (MICS)

14  Goal  monitor progress on the goals adopted at the 1990 World Summit for Children, look at children and their welfare, indicators  Includes topics such as nutrition, child health and mortality, literacy, child protection, etc.  Major international effort- over 100 countries, multiple rounds  Comparability across countries and some add-ons allowed

15  LSMS: community level data to paved and unpaved roads; existence of bus service ◦ Caveat: not on individual preference or expenditure  Overall use or demand for individual transport cannot be determined  HBS/IES: individual expenditures on modes of transport; by rural and urban areas ◦ Caveat: may have no disaggregation per trip type or number of trips taken  Inability to assess mode shares and individual demand as (a) costs related to mode use are aggregated ; (b) movements with no immediate expenditures not recorded (walking; bicycle) and (c) expenditures not equal to trips (private vehicles)

16  HSB/IES: Individual expenditure data by male and female on transport; type of mode used; number of trips ◦ Caveat: S pecific data on number of trips is not always available unless collected in specific individual diaries/’open’ questionnaires  No conclusion can be drawn on whether one form of transport is more or less expensive for men or women

17  LSMS: Individual data on mode of transport, trip purposes and costs for access to education and health facilities, labor- related activities (but not necessarily across countries)  individual data allows disaggregation of data according to gender and provides reasons for not using health care (distance; lack of transport as options)  DHS: individual data on reasons for not using health care (distance; lack of transport as options)  opportunities for geo-referencing with national surveys  MICS: Types of transport and mode owned and used for accessing social and economic activities (education; domestic and household chores – water & food) ◦ Caveat: mainly household data available  Opportunity for custom-questionnaire and questions on reasons for not attending school; not registering children’s birth (distance and travel time as options)

18  The four survey types provide some information on transport access, affordability, trip purposes  No information on quality or safety  Benefits of the four survey types  National level data sets  Ability to link transport use with welfare status, human capital  Ability to track changes over time for specific groups  Not a substitute for transport specific surveys

19  Incorporate additional questions to surveys with focus on gender and transport  Systematize questions as much as possible (International Household Survey Network)  Seek IES/HBS data that is disaggregated by expenditure  Investigate existing data sources before designing full transport survey

20  LSMS  IES/HBS  MICS

21 (% of men and women that made each type of expenditure per week) Source: POF 2002/2003, calculations by authors

22 MalesFemalesAll Bus or taxi School Bus9.4 Private car Bicycle Boat Horse0.3 Walk Other0.1 Source: Encuesta de Niveles de Vida, calculations by authors


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